Computational measures for language similarity across time in online communities

This paper examines language similarity in messages over time in an online com-munity of adolescents from around the world using three computational meas-ures: Spearman’s Correlation Coefficient, Zipping and Latent Semantic Analysis. Results suggest that the participants ’ lan-guage diverges over a six-week period, and that divergence is not mediated by demographic variables such as leadership status or gender. This divergence may represent the introduction of more unique words over time, and is influenced by a continual change in subtopics over time, as well as community-wide historical events that introduce new vocabulary at later time periods. Our results highlight both the possibilities and shortcomings of using document similarity measures to as-sess convergence in language use.